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<li class="toctree-l1"><a class="reference internal" href="modules.html">ultra</a></li>
<li class="toctree-l1"><a class="reference internal" href="input_layer_reference.html">Input Layer Reference</a></li>
<li class="toctree-l1"><a class="reference internal" href="learning_algorithm_reference.html">Learning Algorithm Reference</a></li>
<li class="toctree-l1 current"><a class="current reference internal" href="#">Ranking Model Reference</a><ul>
<li class="toctree-l2"><a class="reference internal" href="#dnn">DNN</a><ul>
<li class="toctree-l3"><a class="reference internal" href="#description">Description</a></li>
<li class="toctree-l3"><a class="reference internal" href="#hyper-parameters">Hyper Parameters</a></li>
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<li class="toctree-l2"><a class="reference internal" href="#linear">Linear</a><ul>
<li class="toctree-l3"><a class="reference internal" href="#id1">Description</a></li>
<li class="toctree-l3"><a class="reference internal" href="#id2">Hyper Parameters</a></li>
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<li class="toctree-l2"><a class="reference internal" href="#dlcm">DLCM</a><ul>
<li class="toctree-l3"><a class="reference internal" href="#id3">Description</a></li>
<li class="toctree-l3"><a class="reference internal" href="#id4">Hyper Parameters</a></li>
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<li class="toctree-l2"><a class="reference internal" href="#gsf">GSF</a><ul>
<li class="toctree-l3"><a class="reference internal" href="#id5">Description</a></li>
<li class="toctree-l3"><a class="reference internal" href="#id6">Hyper Parameters</a></li>
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<li class="toctree-l2"><a class="reference internal" href="#setrank">SetRank</a><ul>
<li class="toctree-l3"><a class="reference internal" href="#id7">Description</a></li>
<li class="toctree-l3"><a class="reference internal" href="#id8">Hyper Parameters</a></li>
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<div class="section" id="ranking-model-reference">
<h1>Ranking Model Reference<a class="headerlink" href="#ranking-model-reference" title="Permalink to this headline">¶</a></h1>
<div class="section" id="dnn">
<h2>DNN<a class="headerlink" href="#dnn" title="Permalink to this headline">¶</a></h2>
<div class="section" id="description">
<h3>Description<a class="headerlink" href="#description" title="Permalink to this headline">¶</a></h3>
<p>The deep neural network model for learning to rank.</p>
<p>This class implements a deep neural network (DNN) based ranking model. It’s essientially a multi-layer perceptron network.</p>
</div>
<div class="section" id="hyper-parameters">
<h3>Hyper Parameters<a class="headerlink" href="#hyper-parameters" title="Permalink to this headline">¶</a></h3>
</div>
</div>
<div class="section" id="linear">
<h2>Linear<a class="headerlink" href="#linear" title="Permalink to this headline">¶</a></h2>
<div class="section" id="id1">
<h3>Description<a class="headerlink" href="#id1" title="Permalink to this headline">¶</a></h3>
<p>A linear model for learning to rank.</p>
<p>This class implements a linear ranking model. It’s essientially a logistic regression model.</p>
</div>
<div class="section" id="id2">
<h3>Hyper Parameters<a class="headerlink" href="#id2" title="Permalink to this headline">¶</a></h3>
</div>
</div>
<div class="section" id="dlcm">
<h2>DLCM<a class="headerlink" href="#dlcm" title="Permalink to this headline">¶</a></h2>
<div class="section" id="id3">
<h3>Description<a class="headerlink" href="#id3" title="Permalink to this headline">¶</a></h3>
<p>The Deep Listwise Context Model for learning to rank.</p>
<p>This class implements the Deep Listwise Context Model (DLCM) for ranking.</p>
<p>See the following paper for more information.</p>
<ul class="simple">
<li><p>Qingyao Ai, Keping Bi, Jiafeng Guo, W. Bruce Croft. 2018. Learning a Deep Listwise Context Model for Ranking Refinement. In Proceedings of SIGIR ‘18</p></li>
</ul>
</div>
<div class="section" id="id4">
<h3>Hyper Parameters<a class="headerlink" href="#id4" title="Permalink to this headline">¶</a></h3>
</div>
</div>
<div class="section" id="gsf">
<h2>GSF<a class="headerlink" href="#gsf" title="Permalink to this headline">¶</a></h2>
<div class="section" id="id5">
<h3>Description<a class="headerlink" href="#id5" title="Permalink to this headline">¶</a></h3>
<p>The Groupwise Scoring Function (with no approaximation) for learning to rank.</p>
<p>This class implements The Groupwise Scoring Function (GSF) based on multi-layer perceptron networks.</p>
<p>See the following paper for more information.</p>
<ul class="simple">
<li><p>Qingyao Ai, Xuanhui Wang, Sebastian Bruch, Nadav Golbandi, Michael Bendersky, Marc Najork. 2019. Learning Groupwise Scoring Functions Using Deep Neural Networks. In Proceedings of ICTIR ‘19</p></li>
</ul>
</div>
<div class="section" id="id6">
<h3>Hyper Parameters<a class="headerlink" href="#id6" title="Permalink to this headline">¶</a></h3>
</div>
</div>
<div class="section" id="setrank">
<h2>SetRank<a class="headerlink" href="#setrank" title="Permalink to this headline">¶</a></h2>
<div class="section" id="id7">
<h3>Description<a class="headerlink" href="#id7" title="Permalink to this headline">¶</a></h3>
<p>The SetRank model for learning to rank.</p>
<p>This class implements the SetRank model for ranking.</p>
<p>See the following paper for more information.</p>
<ul class="simple">
<li><p>Liang Pang, Jun Xu, Qingyao Ai, Yanyan Lan, Xueqi Cheng, Jirong Wen. 2020. SetRank: Learning a Permutation-Invariant Ranking Model for Information Retrieval. In Proceedings of SIGIR ‘20</p></li>
</ul>
</div>
<div class="section" id="id8">
<h3>Hyper Parameters<a class="headerlink" href="#id8" title="Permalink to this headline">¶</a></h3>
</div>
</div>
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